Generative Engine Optimization (GEO)
Generative Engine Optimization (GEO) is the practice of improving how often, how prominently, and how favorably a brand is mentioned in answers generated by AI assistants such as ChatGPT, Gemini, Google AI Overviews, Perplexity, Copilot, and Grok.
Traditional search optimization targets ranked lists of blue links. GEO targets the synthesized answer an AI assistant returns instead, where a model draws on its training data and live retrieval to name specific brands, products, and sources. The unit of success shifts from a page position to whether the model mentions you at all, how it frames you, and which sources it cites.
GEO work spans the signals models rely on: clear and factual content that is easy to extract, consistent brand descriptions across the web, structured data, and presence in the third-party sources assistants tend to retrieve and cite. Because each engine weighs these signals differently, GEO is measured per engine and per query rather than as a single global rank.
A GEO platform such as Brytic tracks a defined set of prompts across multiple assistants, records whether the brand is mentioned, in what position, with what sentiment, and which citations the answer relies on, then reports how those results change over time.